SoroushVahidi/scidocs huggingface dataset:
A Foundation for Multi-dimensional Databases
(1997)

We present a multi-dimensional database model, which we believe can serve as a conceptual model for On-Line Analytical Processing (OLAP)-based applications. Apart from providing the functionalities necessary for OLAP-based applications, the main feature of the model we propose is a clear separation between structural aspects and the contents. This separation of concerns allows us to define data manipulation languages in a reasonably simple, transparent way. In particular, we show that the data cube operator can be expressed easily. Concretely, we define an algebra and a calculus and show them to be equivalent. We conclude by comparing our approach to related work. The conceptual multi-dimensional database model developed here is orthogonal to its implementation, which is not a subject of the present paper.
Regional differences in synaptogenesis in human cerebral cortex.
(1997)

The formation of synaptic contacts in human cerebral cortex was compared in two cortical regions: auditory cortex (Heschl's gyrus) and prefrontal cortex (middle frontal gyrus). Synapse formation in both cortical regions begins in the fetus, before conceptual age 27 weeks. Synaptic density increases more rapidly in auditory cortex, where the maximum is reached near postnatal age 3 months. Maximum synaptic density in middle frontal gyrus is not reached until after age 15 months. Synaptogenesis occurs concurrently with dendritic and axonal growth and with myelination of the subcortical white matter. A phase of net synapse elimination occurs late in childhood, earlier in auditory cortex, where it has ended by age 12 years, than in prefrontal cortex, where it extends to midadolescence. Synaptogenesis and synapse elimination in humans appear to be heterochronous in different cortical regions and, in that respect, appears to differ from the rhesus monkey, where they are concurrent. In other respects, including overproduction of synaptic contacts in infancy, persistence of high levels of synaptic density to late childhood or adolescence, the absolute values of maximum and adult synaptic density, and layer specific differences, findings in the human resemble those in rhesus monkeys.
On shared understanding in software engineering: an essay
(2014)

Shared understanding is essential for efficient software engineering when the risk of unsatisfactory out-come and rework of project results shall be low. Today, however, shared understanding is used mostly in an unreflected, ad-hoc way. This affects the quality of the engineered software solutions and generates re-work once the quality problems are discovered. In this article, we investigate the role, value, and usage of shared understanding in software engineering. We contribute a reflected analysis of the problem, in particular of how to rely on shared understanding that is implicit, rather than explicit. After an overview of the state of the art we discuss forms and value of shared understanding in software engineering, survey enablers and obstacles, compile existing practices for dealing with shared understanding, and present a roadmap for improving knowledge and practice in this area.
Too Much of a Good Thing? The Relationship Between Number of Friends and Interpersonal Impressions on Facebook
(2008)

A central feature of the online social networking system, Facebook, is the connection to and links among friends. The sum of the number of one’s friends is a feature displayed on users’ profiles as a vestige of the friend connections a user has accrued. In contrast to offline social networks, individuals in online network systems frequently accrue friends numbering several hundred. The uncertain meaning of friend status in these systems raises questions about whether and how sociometric popularity conveys attractiveness in non-traditional, non-linear ways. An experiment examined the relationship between the number of friends a Facebook profile featured and observers’ ratings of attractiveness and extraversion. A curvilinear effect of sociometric popularity and social attractiveness emerged, as did a quartic relationship between friend count and perceived extraversion. These results suggest that an overabundance of friend connections raises doubts about Facebook users’ popularity and desirability. Zu viel des Guten? Zur Beziehung zwischen der Anzahl der Freunde und interpersonalen Eindrücken bei Facebook Eine zentrale Eigenschaft des sozialen Online-Netzwerks Facebook ist die Verbindung von Freunden. Die Gesamtanzahl der Freunde eines Nutzers wird als Merkmal im Benutzerprofil angezeigt und dient als eine Statistik der Freundeverbindungen, die ein Nutzer gesammelt hat. Im Gegensatz zu Offline-Netzwerken, haben Personen in OnlineNetzwerken oft mehrere Hundert Freunde. Die unklare Bedeutung des Freundestatus in diesem System wirft die Frage auf, ob und wie soziometrische Popularität die Attraktivität auf nicht-traditionelle, nichtlineare Weise ausdrückt. In einem Experiment wurde die Beziehung zwischen der Anzahl der Freunde im Facebook-Profil und der Einschätzung von Attraktivität und Extraversion durch den Beobachter untersucht. Es zeigten sich ein kurvilinearer Effekt von soziometrischer Popularität und sozialer Attraktivität, sowie eine biquatratische Beziehung zwischen der Anzahl der Freunde und wahrgenommener Extraversion. Diese Ergebnisse deuten an, dass eine übermäßig hohe Zahl an Freunden Zweifel an der Popularität und Attraktivität des Facebook-Nutzers
Crossbar RRAM Arrays: Selector Device Requirements During Write Operation
(2014)

A comprehensive analysis of write operations (SET and RESET) in a resistance-change memory (resistive random access memory) crossbar array is carried out. Three types of resistive switching memory cells-nonlinear, rectifying-SET, and rectifying-RESET-are compared with each other in terms of voltage delivery, current delivery, and power consumption. Two different write schemes, V/2 and V/3, were considered, and the V/2 write scheme is preferred due to much lower power consumption. A simple numerical method was developed that simulates entire current flows and node voltages within a crossbar array and provides a quantitative tool for the accurate analysis of crossbar arrays and guidelines for developing reliable write operation.
Segmentation quality evaluation based on multi-scale convolutional neural networks
(2017)

Segmentation quality evaluation is an important task in image segmentation. The existing evaluation methods formulate segmentation quality as regression model, and recent Convolutional Neural Network (CNN) based evaluation methods show superior performance. However, designing efficient CNN-based segmentation evaluation model is still under exploited. In this paper, we propose two types of CNN structures such as double-net and multi-scale network for segmentation quality evaluation. We observe that learning the local and global information and considering multi-scale image are useful for segmentation quality evaluation. To train and verify the proposed networks, we construct a novel objective segmentation quality evaluation dataset with large amount of data by combining several proposal generation methods. The experimental results demonstrate that the proposed method obtains larger Linear Correlation Coefficient (LCC) value than several state-of-art segmentation quality evaluation methods.
Exploring Hypergraph Representation on Face Anti-spoofing Beyond 2D Attacks
(2018)

Face anti-spoofing plays a crucial role in protecting face recognition systems from various attacks. Previous modelbased and deep learning approaches achieve satisfactory performance for 2D face spoofs, but remain limited for more advanced 3D attacks such as vivid masks. In this paper, we address 3D face anti-spoofing via the proposed Hypergraph Convolutional Neural Networks (HGCNN). Firstly, we construct a computation-efficient and posture-invariant face representation with only a few key points on hypergraphs. The hypergraph representation is then fed into the designed HGCNN with hypergraph convolution for feature extraction, while the depth auxiliary is also exploited for 3D mask anti-spoofing. Further, we build a 3D face attack database with color, depth and infrared light information to overcome the deficiency of 3D face anti-spoofing data. Experiments show that our method achieves the state-of-theart performance over widely used 3D and 2D databases as well as the proposed one under various tests.
A review of eye-tracking applications as tools for training
(2012)

Substantial literature exists regarding how eye-tracking systems can be used to measure cognitive load and how these measurements can be useful for adapting training in real time. Much of the published literature discusses the applications and limitations of the research and typically provides recommendations for improvement. This review assesses these articles collectively to provide a clearer solution for implementing eye-tracking systems into a training environment. Although limitations exist for using eye tracking as an interface tool, gaze and pupillary response have been successfully used to reflect changes in cognitive load and are starting to be incorporated into adaptive training systems, although issues are still present with differentiating pupil responses from simultaneous psychological effects. Additionally, current eye-tracking systems and data analysis software have proven accurate enough for general use, but issues including system cost and software integration prevent this technology from becoming commercialized for use in common instructional settings.
Waveguide slot antennas for circularly polarized radiated field
(2004)

We present a new waveguide slot configuration able to radiate a circular polarization with a very low axial ratio. This configuration is mainly intended as a circularly polarized radiating element to be used in an array. Both left-hand and right-hand circular polarization can be independently obtained and therefore this configuration could be used to realize a polarization agile antenna. The proposed configuration consists of two very closely spaced radiating slots, so a specialized method of moments code has been developed to analyze, in a very effective way, the near-field interaction between such slots. Our method of moments code has been validated against a commercial finite-element method code, and then used to design a number of different circularly polarized radiating elements.
Evaluating the Readability of Text Simplification Output for Readers with Cognitive Disabilities
(2016)

This paper presents an approach for automatic evaluation of the readability of text simplification output for readers with cognitive disabilities. First, we present our work towards the development of the EasyRead corpus, which contains easy-to-read documents created especially for people with cognitive disabilities. We then compare the EasyRead corpus to the simplified output contained in the LocalNews corpus (Feng, 2009), the accessibility of which has been evaluated through reading comprehension experiments including 20 adults with mild intellectual disability. This comparison is made on the basis of 13 disability-specific linguistic features. The comparison reveals that there are no major differences between the two corpora, which shows that the EasyRead corpus is to a similar reading level as the user-evaluated texts. We also discuss the role of Simple Wikipedia (Zhu et al., 2010) as a widely-used accessibility benchmark, in light of our finding that it is significantly more complex than both the EasyRead and the LocalNews corpora.
Wafer-scale VLSI implementations of pulse coupled neural networks
(2007)

In this paper, we present a system architecture currently under development that will allow very large (>10 neurons, >10 synapses) reconfigurable networks to be built, in the form of interlinked dies on a single wafer. Reconfigurable routing and complex adaptation/plasticity across several timescales in neurons and synapses allow for the implementation of large-scale biologically realistic neuronal networks and behaviors. Compared to biology the network dynamics will be about 10 to 10 times faster, so that developmental plasticity can be studied in detail. Keywords—neural VLSI hardware, system simulation, mapping algorithms, parallelization.
Escher sphere construction kit
(2001)

M.C. Escher created a myriad of amazing planar tessellations, yet only a few three-dimensional ones such as his wooden fish ball and dodecahedral flower. We have developed an interactive program to design and manufacture “Escher Spheres” sets of tiles that can be assembled into spherical balls. The user chooses from a set of predefined symmetry groups and then deforms the boundaries of the basic domain tile; all corresponding points based on the chosen symmetry class move concurrently, instantly showing the overall result. The interior of the tile can be embellished with a bas-relief. Finally the tile is radially extruded and output as a solid model suitable for free-form fabrication.
Comparative study of algorithms for Atrial Fibrillation detection
(2011)

Automatic detection of Atrial Fibrillation (AF) is necessary for the long-term monitoring of patients who are suspected to have AF. Several methods for AF detection exist in the literature. These methods are mainly based on two different characteristics of AF ECGs: the irregularity of RR intervals (RRI) and the fibrillatory electrical Atrial Activity (AA). The electrical AA is characterized by the absence of the P-wave (PWA) and special frequency properties (FSA). Nine AF detection algorithms were selected from literature and evaluated with the same protocol in order to study their performance under different conditions. Results showed that the highest sensitivity (Se=97.64%) and specificity (Sp=96.08%) was achieved with methods based on analysis of irregularity of RR interval, while combining RR and atrial activity analysis gave the highest positive predictive value (PPV=92.75%). Algorithms based on RR irregularity were also the most robust against noise (Se=85.79% and Sp=81.90% for SNR=0dB; and Se=82.52% and Sp=40.47% for SNR=−5dB).
Resource management in a changing and uncertain climate
(2010)

© The Ecological Society of America www.frontiersinecology.org C change has already had important effects on ecological systems (Parmesan 2006; Root and Schneider 2006; IPCC 2007a; Rosenzweig et al. 2008). Projected changes in climate for the coming century are all greater than the climatic changes the Earth has experienced in the past 100 years (IPCC 2007b). Consequently, future changes in climate are likely to result in even more dramatic ecological responses, including declines in particularly sensitive species (eg corals), continued shifts in species distributions, and substantial changes in ecosystem processes (IPCC 2007a). Changes in hydrologic and fire regimes will fundamentally alter ecological systems. Sea-level rise, in particular, will have dramatic effects on coastal systems (Watson et al. 1996). Changes in phenology will affect the delicate relationships between pollinators and plants, parasites and hosts, foragers and forage, and predators and prey (eg Memmott et al. 2007). Despite the pervasiveness of climate change, most land, water, and resource managers are still following management plans that were developed before there was a scientific consensus that climate-change impacts were both real and substantial (Pyke et al. 2008). Climate change poses difficult challenges for many already overstretched natural resource managers, who must deal with day-to-day crises and who have little access to climate experts. Much of the widely available information about climate change focuses on global or regional scales that are often too broad to fully inform the management of specific nature reserves or regional forests. Moreover, much of the information that is available has a high level of uncertainty, and thus can be difficult to interpret. Finally, although climate change is having impacts today, the largest impacts are still decades in the future. Envisioning these impacts and acting well in advance of their realization will require a new level of proactive management. Several articles have provided general recommendations for managing particular systems in a changing climate (Noss 2001; Hannah et al. 2002; West and Salm REVIEWS REVIEWS REVIEWS
A Smart Fridge with an Ability to Enhance Health and Enable Better Nutrition
(2009)

Intelligent appliances with multimedia capability have been emerging into our daily life, thanks to the fast advance of computing technology and the wide use of the Interne. Smart home is one of the most prominent areas of intelligent appliances. Kitchen is one of the places where such intelligent appliances have been used. Since modern life style is driving people spending less time on cooking healthy food at home, an enjoyable and healthy life style can be assisted with an intelligent kitchenware such as a smart fridge. In this paper we introduce a novel idea of the smart fridge which can enable better nutrition and enhance health. It is designed for managing items stored in it and advising its users with cooking methods depending on what kind of food is stored. More importantly, it can perform other actions such as dietary control, nutrition monitoring, eating habit analysis, etc. The characteristics, functions and design details of the smart fridge are presented in details. We are confident that such a smart fridge will be an important component in future smart home.
Review: A Review of Culture in Information Systems Research: Toward a Theory of Information Technology Culture Conflict
(2006)

An understanding of culture is important to the study of information technologies in that culture at various levels, including national, organizational, and group, can influence the successful implementation and use of information technology. Culture also plays a role in managerial processes that may directly, or indirectly, influence IT. Culture is a challenging variable to research, in part because of the multiple divergent definitions and measures of culture. Notwithstanding, a wide body of literature has emerged that sheds light on the relationship of IT and culture. This paper sets out to provide a review of this literature in order to lend insights into our understanding of the linkages between IT and culture. We begin by conceptualizing culture and laying the groundwork for a values-based approach to the examination of IT and culture. Using this approach, we then provide a comprehensive review of the organizational and cross-cultural IT literature that conceptually links these two traditionally separate streams of research. From our analysis, we develop six themes of IT-culture research emphasizing culture's impact on IT, IT's impact on culture, and IT culture. Building upon these themes, we then develop a theory of IT, values, and conflict. Based upon the theory, we develop propositions concerning three types of cultural conflict and the results of these conflicts. Ultimately, the theory suggests that the reconciliation of these conflicts results in a reorientation of values. We conclude with the particular research challenges posed in this line of inquiry.
Multivariate data analysis of NMR data.
(1991)

Multivariate methods based on principal components (PCA and PLS) have been used to reduce NMR spectral information, to predict NMR parameters of complicated structures, and to relate shift data sets to dependent descriptors of biological significance. Noise reduction and elimination of instrumental artifacts are easily performed on 2D NMR data. Configurational classification of triterpenes and shift predictions in disubstituted benzenes can be obtained using PCA and PLS analysis. Finally, the shift predictions of tripeptides from descriptors of amino acids open the possibility of automatic analysis of multidimensional data of complex structures.
Preserving differential privacy in convolutional deep belief networks
(2017)

The remarkable development of deep learning in medicine and healthcare domain presents obvious privacy issues, when deep neural networks are built on users’ personal and highly sensitive data, e.g., clinical records, user profiles, biomedical images, etc. However, only a few scientific studies on preserving privacy in deep learning have been conducted. In this paper, we focus on developing a private convolutional deep belief network (pCDBN), which essentially is a convolutional deep belief network (CDBN) under differential privacy. Our main idea of enforcing $$\epsilon $$ ϵ -differential privacy is to leverage the functional mechanism to perturb the energy-based objective functions of traditional CDBNs, rather than their results. One key contribution of this work is that we propose the use of Chebyshev expansion to derive the approximate polynomial representation of objective functions. Our theoretical analysis shows that we can further derive the sensitivity and error bounds of the approximate polynomial representation. As a result, preserving differential privacy in CDBNs is feasible. We applied our model in a health social network, i.e., YesiWell data, and in a handwriting digit dataset, i.e., MNIST data, for human behavior prediction, human behavior classification, and handwriting digit recognition tasks. Theoretical analysis and rigorous experimental evaluations show that the pCDBN is highly effective. It significantly outperforms existing solutions.
Gate sizing: finFETs vs 32nm bulk MOSFETs
(2006)

FinFET devices promise to replace traditional MOSFETs because of superior ability in controlling leakage and minimizing short channel effects while delivering a strong drive current. We investigate in this paper gate sizing of finFET devices, and we provide a comparison with 32nm bulk CMOS. Wider finFET devices are built utilizing multiple parallel fins between the source and drain. Independent gating of the finFET's double gates allows significant reduction in leakage current. We perform temperature-aware circuit optimization by modeling delay using temperature-dependent parameters, and by imposing constraints that limit the maximum allowable number of parallel fins. We show that finFET circuits are superior in performance and produce less static power when compared to 32nm circuits.
An evolutionary artificial neural networks approach for breast cancer diagnosis
(2002)

This paper presents an evolutionary artificial neural network (EANN) approach based on the pareto-differential evolution (PDE) algorithm augmented with local search for the prediction of breast cancer. The approach is named memetic pareto artificial neural network (MPANN). Artificial neural networks (ANNs) could be used to improve the work of medical practitioners in the diagnosis of breast cancer. Their abilities to approximate nonlinear functions and capture complex relationships in the data are instrumental abilities which could support the medical domain. We compare our results against an evolutionary programming approach and standard backpropagation (BP), and we show experimentally that MPANN has better generalization and much lower computational cost.